readme.md

timer-trigger-cosmosdb-output-binding (Python)

Sample	Description	Trigger	In Bindings	Out Bindings
timer-trigger-cosmos-output-binding	Azure Functions Timer Trigger Python Sample. The function gets blog RSS feed and store the results into CosmosDB using Cosmos DB output binding	Timer	NONE	CosmosDB

How it works

For a TimerTrigger to work, you provide a schedule in the form of a cron expression(See the link for full details). A cron expression is a string with 6 separate expressions which represent a given schedule via patterns. The pattern used in this sample (0 1 * * * *) is to represent "once a day at 1:00 am". The following is Cron schedule pattern samples:

# every 5 minutes
0 */5 * * * *

# Run every 6 hours at 10 mins past the hour
10 */6 * * * *

# Run at 1:00 am
0 1 * * * *

# Run at 5:31 pm:
31 17 * * * *

Configurations

As specified in functions.json, you need Azure Cosmos DB account for storing data using Cosmos DB output binding

{
  "scriptFile": "__init__.py",
  "bindings": [
    {
      "name": "mytimer",
      "type": "timerTrigger",
      "direction": "in",
      "schedule": "0 1 * * * *"
    },
    {
      "direction": "out",
      "type": "cosmosDB",
      "name": "outdoc",
      "databaseName": "testdb",
      "collectionName": "feedcol",
      "leaseCollectionName": "leases",
      "createLeaseCollectionIfNotExists": true,
      "connectionStringSetting": "MyCosmosDBConnectionString",
      "createIfNotExists": true
    }
  ]
}

Create Cosmos DB Account and DB & Collection for testing

Create a Cosmos DB Account

COSMOSDB_ACCOUNT_NAME="azfuncv2db"
RESOURCE_GROUP="RG-azfuncv2"
az cosmosdb create \
    --name $COSMOSDB_ACCOUNT_NAME \
    --kind GlobalDocumentDB \
    --resource-group $RESOURCE_GROUP

Create Database and Collection in the Cosmos DB that you've created

# Get Key
COSMOSDB_KEY=$(az cosmosdb list-keys --name $COSMOSDB_ACCOUNT_NAME --resource-group $RESOURCE_GROUP --output tsv |awk '{print $1}')

# Create Database
az cosmosdb database create \
    --name $COSMOSDB_ACCOUNT_NAME \
    --db-name $DATABASE_NAME \
    --key $COSMOSDB_KEY \
    --resource-group $RESOURCE_GROUP

# Create a container with a partition key and provision 400 RU/s throughput.
COLLECTION_NAME="feedcol"
az cosmosdb collection create \
    --resource-group $RESOURCE_GROUP \
    --collection-name $COLLECTION_NAME \
    --name $COSMOSDB_ACCOUNT_NAME \
    --db-name $DATABASE_NAME \
    --partition-key-path /title \
    --throughput 400

# Create a container for leaves
# 'leaves' need to be a single collection partition
# Please see also: https://github.com/Azure/azure-functions-core-tools/issues/930
LEASES_COLLECTION_NAME="leases"
az cosmosdb collection create \
    --resource-group $RESOURCE_GROUP \
    --collection-name $LEASES_COLLECTION_NAME \
    --name $COSMOSDB_ACCOUNT_NAME \
    --db-name $DATABASE_NAME \
    --throughput 400

How to develop and publish the function

Local development

func host start

Publish the function to the cloud

Publish the function to the cloud

FUNCTION_APP_NAME="MyFunctionApp"
func azure functionapp publish $FUNCTION_APP_NAME --build-native-deps --no-bundler

Add Functions App Settings

COSMOS_DB_CONNECTION="***************"
az webapp config appsettings set \
  -n $FUNCTION_APP_NAME \
  -g $RESOURCE_GROUP \
  --settings \
    MyCosmosDBConnectionString=$COSMOS_DB_CONNECTION

Sample output data stored in CosmosDB

If all goes successfully and feed results are stored in the Cosmos DB that you've created, you'll see the document like this:

{
    "items": [
        {
            "id": "dbe7a29c0de2807a5f17e9a3a63bc5f3378bc815",
            "title": "Blog: Update on Volume Snapshot Alpha for Kubernetes",
            "date": "Thu, 17 Jan 2019 00:00:00 +0000"
        },
        {
            "id": "9eda61a9ba684f1acb9a03c8b709f51df80c905a",
            "title": "Blog: Container Storage Interface (CSI) for Kubernetes GA",
            "date": "Tue, 15 Jan 2019 00:00:00 +0000"
        },
        {
            "id": "6c24aea9a7d60f8697c3cfe5328e1c86196facbc",
            "title": "Blog: APIServer dry-run and kubectl diff",
            "date": "Mon, 14 Jan 2019 00:00:00 +0000"
        },
        {
            "id": "00c9181702e3e237bb150d248ffcc27796f8774f",
            "title": "Blog: Kubernetes Federation Evolution",
            "date": "Wed, 12 Dec 2018 00:00:00 +0000"
        },
        {
            "id": "fe818ab1fb07e0a95e2a0e7bf754c15ab95bf6b8",
            "title": "Blog: etcd: Current status and future roadmap",
            "date": "Tue, 11 Dec 2018 00:00:00 +0000"
        }
    ],
    "id": "ab8f4110-0692-4875-9d0f-b864cca603c6",
    "_rid": "dCoKAPwUdioBAAAAAAAAAA==",
    "_self": "dbs/dCoKAA==/colls/dCoKAPwUdio=/docs/dCoKAPwUdioBAAAAAAAAAA==/",
    "_etag": "\"0d004e82-0000-0000-0000-5c544bf70000\"",
    "_attachments": "attachments/",
    "_ts": 1549028343
}